Research Article Influence of Caprock Morphology on Solubility Trapping during CO 2 Geological Sequestration Pradeep Reddy Punnam , Balaji Krishnamurthy , and Vikranth Kumar Surasani Department of Chemical Engineering, Birla Institute of Technology and Science, Pilani-Hyderabad Campus, 500078, Hyderabad, India Correspondence should be addressed to Vikranth Kumar Surasani; surasani@hyderabad.bits-pilani.ac.in Received 24 August 2021; Revised 27 May 2022; Accepted 30 May 2022; Published 24 June 2022 Academic Editor: Ondra Sracek Copyright © 2022 Pradeep Reddy Punnam et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Carbon capture and sequestration (CCS) technology is one of the indispensable alternatives to reduce carbon dioxide (CO 2 ) emissions. In this technology, carbon capture and transport grid will send CO 2 to the storage facilities that are using various storage techniques. Geologic carbon sequestration (GCS) is one such storage technique where CO 2 is injected into a deep geological subsurface formation. The injected CO 2 is permanently stored in the formation due to structural, residual, solubility, and mineral trapping phenomena. Among different trapping mechanisms, solubility trapping plays a significant role in the safe operation of GCS. In this work, the study is conducted to elucidate the influence of top surface caprock morphology on the solubility trapping mechanism. The simulation results show that the naturally available heterogeneous formations with anticline and without anticline structure influence the solubility fingering phenomena and solubility entrapment percentage over a geological time scale. The lateral migration and sweeping efficiency results of both the synthetic domains for the injected CO 2 have shown the importance of caprock morphology on solubility trapping and selection of injection rate. Quantification of solubility trapping in two morphological structures revealed that the synthetic domain without anticline morphology had shown higher solubility trapping. In the future, the simulation data using Artificial Neural Networks can be applied to predict the structural and solubility trapping of geological formations. This analysis further helps incorporating the interaction of CO 2 with porous media leading to a mineral trapping mechanism. 1. Introduction Carbon capture, utilization, and sequestration (CCUS) tech- nology is an emerging field to mitigate the CO 2 emissions into the earth’s atmosphere. Precombustion, oxy-fuel com- bustion, postcombustion, and chemical loop combustion are four widely used carbon capture technologies [1, 2]. Post capture, in carbon utilization technologies, CO 2 is chemi- cally transformed into other value-added products, mostly fuels like hydrogen, methanol, and synthetic natural gas [2, 3]. However, the carbon utilization technologies are in an emerging stage that needs new novel catalyst developments and scale-up procedures to meet the current emission rate. Alternatively, in carbon sequestration technology, CO 2 can be stored in deep sea beds and geological formations and used in Enhanced-Oil-Recovery (EOR), methane recovery from coal seams, etc. [2]. Among carbon sequestration tech- nologies, the geologic CO 2 sequestration (GCS) is the most viable option to permanently dispose CO 2 in deep geological formations [4, 5]. Upon implementation of carbon capture and sequestration (CCS) technology, it can effectively decrease the social cost of carbon value. Despite having the potential to be a mainstream technology for reducing CO 2 emissions, the CCS also has barriers and hurdles in imple- mentation in most countries. The transportation and setup cost of the injection grid is financially expensive [6]. During postinjection period, a dedicated monitoring and disaster unit has to be established to monitor the migration and con- trol the leakage of CO 2 from the subsurface [6]. The accep- tance rate from the public communities for the technology is slim because of the unawareness and low confidence in the technology [6, 7]. Hindawi Geofluids Volume 2022, Article ID 8016575, 15 pages https://doi.org/10.1155/2022/8016575